Logistics regression | Mathematics homework help

Complete Smart Alex’s Task #6 on p. 812 to complete the logistic multiple regression analysis exercise using the condom.sav dataset from the Field text. You can follow the steps outlined on p. 799 as a guide. Report your findings in APA format according to the guidelines in the PASW Application Assignment Guidelines handout. The final document should be 2–3 pages long.

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 conduct (a Binary) Logistical Regression analysis employing the Condom.sav date file.

The variable Use (Condom Use, 0 = Unprotected, 1 = Used Condom) is the dependent variable

There are six predictor variables (covariates) of condom use; they are:

1) Safety: See page 813 in the Field text for a description of the variable.

2) Gender ; 0 = male, and 1 = female.

3) Sexexp:  See page 813 in the Field text for a description of the variable.

4) Previous: a nominal measure indicated whether or not the couple used a condom in the past.  Because this variable has 3 levels (0 = not used, 1 = used condom, and 2 = no previous sexual experience with the partner), it would be designated as a categorical variable (pages 776-778, in Field text).  However, because there are only three cases in category 2 (First Time with Partner), you can set the value 2 to be a missing value.  You learned how to set variables values to missing in RSCH82000 (If you don’t remember how, see pages 107-108 in the Field text.  Also see the attached SPSS data file, and you’ll notice that I’ve set 2 as a missing value for the variable Previous.

5) Selfcon: See page 813 in the Field text for a description of the variable.

6) Perceive:  See page 813 in the Field text for a description of the variable.

You must read the descriptions of these variables on page 813 in the Field text in order to interpret the findings.

You must be able to create the following Syntax.

LOGISTIC REGRESSION VARIABLES use
 /METHOD=ENTER safety gender sexexp previous selfcon perceive
 /PRINT=GOODFIT CI(95)
 /CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).

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